Support vector machine algorithms to automatically identify each artifact were written using the Machine Learning MATLAB R2011 Toolbox. Artifacts were artificially introduced in the images during the reconstruction process using iTool reconstructor. The images were acquired during two months. 14 KV CBCTs from the Emma phantom were obtained using a TrueBeam onboard imager as example of data acquisition and analysis. Hardware was developed that allowed the localization of several phantoms simultaneously on the couch. MATLAB R013B was used to develop an interface that could allow the data to be processed and analyzed. XML scripts were written and used in developer mode in a TrueBeam linac to automatically acquire data. A three-step paradigm where the data are automatically acquired, processed, and analyzed was defined. Daily and monthly imaging QA for SRS and SBRT protocols were fully automated on a Varian linac. The purpose of this study was to automate regular Imaging QA procedures to become more efficient and accurate.

Itools 4 will enable developer mode